Relacion entre big data y internet of things

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this data is digitized

The next step will be artificial intelligence using Big Data enabled by the first three elements.Artificial Intelligence does not replace human intelligence; it is just a tool that augments human intelligence in an effort to benefit humanity. Artificial Intelligence is the way we make sense of unstructured data and turn it into intelligence from which, we can create innovation and transformation.From improving the quality of life (such as, for example, effectively managing smart buildings) to solving social problems (such as environmental problems), Artificial Intelligence will change the rules of the game.5.

biggest big data companies

Ever since analysts and especially Gartner began publishing their interpretation of “Technology Cycles” to help us discern the hype of what is commercially viable, new technologies have been appearing all the time. Over time some have become relevant, but at other times they have not been adopted by customers and have been forgotten without being able to demonstrate that they were capable of solving the real business problems they promised.

First we must understand that things are either sensors or actuators. A sensor is a device that is able to detect external actions or stimuli and respond accordingly. These devices can transform physical or chemical quantities into electrical quantities. Think of a temperature sensor, or even the GPS receiver in your cell phone. On the other hand an actuator is a device capable of transforming this electrical energy into the activation of a process in order to generate an effect on an automated process.

companies using big data and artificial intelligence

Organizations are combining the agility of big data with the scalability of artificial intelligence. And their executives are adapting to the interrelationship between both elements, betting on their results. As is well known, information is power.

The processes of organizations have within their reach to implement artificial intelligence techniques that offer competitive advantages and objective interpretation of data for decision making, among others.

Big data architectures enable the implementation and management of data, within the business strategy of digitization. If dashboards and reports are underpinned by efficient, secure, truthful and quality data analysis, the decision-making process will benefit from it all.

Digitalization has profoundly changed the scenario and has forced companies to hire the services of professionals who, based on a huge amount of information, manage, analyze and integrate it into the day-to-day running of the organization and its decision-making processes.

what is big data

These trends are quite pervasive and explain many of the disruptions occurring in industries. But they are especially applicable to big data. The term “big data” does not only refer to gigantic data sets and exotic software. It also means treating data as an infrastructure: centralized, secure, massive in scale, and built as a general resource rather than for a specific end use. It also requires treating the inference process as a “superstructure”: iterative, tactical, granular, modular and decentralized. If you conflate the two internally, you are replacing a product-based or market-based organization with a functional organization. If they are combined externally, the result is a fundamental challenge – a disruption – to many traditional business models.

In this essay I propose to explain in a general way the logic of deconstruction and polarization of scale and then apply it to the specific case of big data. I hope that by stepping back to broaden the perspective, we can appreciate its long-term strategic and organizational importance.

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